Statistical colocalization of monocyte gene expression and genetic risk variants for type 1 diabetes

Abstract

One mechanism by which disease-associated DNA variation can alter disease risk is altering gene expression. However, linkage disequilibrium (LD) between variants, mostly single-nucleotide polymorphisms (SNPs), means it is not sufficient to show that a particular variant associates with both disease and expression, as there could be two distinct causal variants in LD. Here, we describe a formal statistical test of colocalization and apply it to type 1 diabetes (T1D)-associated regions identified mostly through genome-wide association studies and expression quantitative trait loci (eQTLs) discovered in a recently determined large monocyte expression data set from the Gutenberg Health Study (1370 individuals), with confirmation sought in an additional data set from the Cardiogenics Transcriptome Study (558 individuals). We excluded 39 out of 60 overlapping eQTLs in 49 T1D regions from possible colocalization and identified 21 coincident eQTLs, representing 21 genes in 14 distinct T1D regions. Our results reflect the importance of monocyte (and their derivatives, macrophage and dendritic cell) gene expression in human T1D and support the candidacy of several genes as causal factors in autoimmune pancreatic beta-cell destruction, including AFF3, CD226, CLECL1, DEXI, FKRP, PRKD2, RNLS, SMARCE1 and SUOX, in addition to the recently described GPR183 (EBI2) gene.

Genetic-Variation-Driven Gene-Expression Changes Highlight Genes with Important Functions for Kidney Disease

“…40,41 In short, coloc uses summary statistics to test for colocalization of GWAS and eQTL signals with the LD information. Coloc supports multiple hypotheses and can distinguish insufficient association from colocalization or distinct associations.…”

“…To address the latter issue, we also implemented a Bayesian method, coloc, 40,41 to formally test the hypothesis of association of a given region with eQTL and GWAS signals. Due to the nature of the analyses, we could only import one study from GWAS analyses instead of using our curated list with a multiple cohort of studies.…”

Regulation of the imprinted Dlk1-Dio3 locus by allele-specific enhancer activity

“…A role for AFF3 in imprinted gene expression in humans is indicated by the existence of SNPs in AFF3 regulatory regions that are associated with human autoimmune diseases, including rheumatoid arthritis, systemic lupus erythematosus, and type 1 diabetes (Stahl et al 2010;Cen et al 2012;Wallace et al 2012). These diseases are themselves linked to changes in imprinted gene expression (Camprubi and Monk 2011), raising the possibility that their etiology could result from misregulation of AFF3 at regulatory regions of imprinted genes.…”

Renalase

“…Most importantly, it identified 18 novel loci, and the strongest evidence of association among these novel regions was achieved at rs10509540 (combined P =1.3×10 −28 ), located on chromosome 10q23.31 in the renalase (RNLS) gene [19]. In another recent study, a statistical test of colocalization was applied to type 1 diabetes-associated regions and confirmed a potential role for renalase in the development of autoimmune pancreatic β-cell destruction [20]. Outside the HLA region, RNLS, rs10509540, and the IL2 SNP rs2069763 have been shown to have an age-at-diagnosis effect on pediatric-onset type 1 diabetes, and for both loci, subjects with the susceptible homozygous phenotype were diagnosed ~7 months earlier than those with the protective genotypes [21 ▪ ].…”